A Bioleaching Process for Sustainable Recycling of Complex Structures with Multi-Metal Layers
Bibliographic record
Abstract
Industrial waste is accumulating, while primary metal resources are depleting. Bioleaching has been shown to be a cost-effective and environmentally friendly approach to metal recovery from waste, but improved designs are needed for large-scale recycling. Metal components that are manufactured by electrodeposition over a mandrel can be difficult to recycle using conventional techniques due to their complex geometry and inner Ag coating. A sustainable biotechnology for separating Cu and Ag from waste electrodeposited components is presented. Two-step bioleaching experiments were performed, during which Cu was solubilized by Fe3+ regenerated by Acidithiobacillus (At.) ferrooxidans CF3 and a consortium of ten acidophilic Fe2+-oxidizers. High Cu recovery rates were achieved in agitated flasks (22 °C, pH 1.9), with At. ferrooxidans solubilizing 94.7% Cu in 78 days and the consortium 99.2% Cu in 59 days. Copper bio-solubilization was significantly accelerated in a laboratory-scale bioreactor (32 °C, 1 L air min−1) using the bacterial consortium adapted to elevated Cu concentrations, reaching >99.6% Cu extraction in only 12 days. The bioreactor was dominated by Leptospirillum and Acidithiobacillus, with their proportions changing (from 83.2 to 59% of total reads and from 3.6 to 29.4%, respectively) during the leaching process. Dissolved Cu was recovered from the bioleachates (containing 14 to 22 g Cu L−1) using electrowinning; >99% of the Cu was deposited (with Cu purity of 98.5 to 99.9%) in 3.33 h (at current efficiency between 80 and 92%). The findings emphasize the importance of a bioleaching system design to achieve economical separation of base and precious metals from industrial wastes. The presented technology minimizes waste generation and energy consumption. On a larger scale, it has the potential to contribute to the development of industrial recycling processes that will protect natural resources and contribute to the Net Zero target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".